summaryrefslogtreecommitdiff
path: root/runtimes/libs/ARMComputeEx/arm_compute/runtime/CL/functions/CLTransposeConvLayer.h
blob: 340a7bfe9025a413aa818d5b7d0a94fa585030b0 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
/*
 * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
 * Copyright (c) 2017-2018 ARM Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#ifndef __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__
#define __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__

#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
#include "arm_compute/runtime/CL/functions/CLTransposeConvLayerUpsample.h"

#include "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h"

#include "arm_compute/runtime/CL/CLMemoryGroup.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"

#include <memory>

namespace arm_compute
{
class ICLTensor;
/** Function to run the transpose convolution layer.
 *
 * @note This layer was copied in order to fix a bug computing to wrong output dimensions.
 *
 * TransposeConv Layer is the backward pass of Convolution Layer. First we transform the input
 * depending on the stride and pad info and then perform a 1x1
 * convolution pass. Input stride defines how many zeroes we should put between each element of the
 * input, pad is the amount of padding and finally a is a user
 * specified value where a < stride - 1, that increases the padding top and right of the input
 * image.
 *
 *  The relation between input to output is as follows:
 *  \f[
 *       width\_output = (width\_input - 1) \cdot stride\_x - \cdot padding\_x + kernel\_x
 *  \f]
 *  \f[
 *       height\_output = (height\_input - 1) \cdot stride\_y - \cdot padding\_y + kernel\_y
 *  \f]
 *
 *  where:
 *      width_input is the size of the first input dimension.
 *      height_input is the size of the second input dimension.
 *      width_output is the size of the first output dimension.
 *      height_output is the size of the second output dimension.
 *      kernel_x and kernel_y are the convolution sizes in x and y.
 *      stride_x and stride_y is the input stride of the first and second dimension.
 *
 * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution.
 * Therefore, it will be necessary to use the weights in the
 * reverse order to perform an actual convolution. This is achieved by using the @ref
 * CPPFlipWeightsKernel.
 *
 * This function calls the following OpenCL kernels/functions:
 *
 * -# @ref CLTransposeConvLayerUpsample
 * -# @ref CLConvolutionLayer
 *
 */
class CLTransposeConvLayer : public IFunction
{
public:
  /** Constructor */
  CLTransposeConvLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
  /** Prevent instances of this class from being copied (As this class contains pointers) */
  CLTransposeConvLayer(const CLTransposeConvLayer &) = delete;
  /** Default move constructor */
  CLTransposeConvLayer(CLTransposeConvLayer &&) = default;
  /** Prevent instances of this class from being copied (As this class contains pointers) */
  CLTransposeConvLayer &operator=(const CLTransposeConvLayer &) = delete;
  /** Default move assignment operator */
  CLTransposeConvLayer &operator=(CLTransposeConvLayer &&) = default;
  /** Set the input, weights, biases and output tensors.
   *
   * @param[in,out] input          Input tensor. 3 lower dimensions represent a single input,
   *                               and an optional 4th dimension for batch of inputs.
   *                               Data types supported: QASYMM8/F16/F32.
   * @param[in]     weights        The 4d weights with dimensions [width, height, IFM, OFM].
   *                               Data type supported: Same as @p input.
   * @param[in]     bias           (Optional) The biases have one dimension. Data type supported:
   *                               Same as @p input.
   * @param[out]    output         Output tensor. The output has the same number of dimensions
   *                               as the @p input.
   * @param[in]     info           Contains padding and policies to be used in the
   *                               transpose convolution, this is decribed in @ref PadStrideInfo.
   * @param[in]     invalid_right  The number of zeros added to right edge of the output.
   * @param[in]     invalid_bottom The number of zeros added to top edge of the output.
   * @param[in]     weights_info   (Optional) Weights information needed for @ref
   *                               CLConvolutionLayer, specifies if the weights tensor has been
   *                               reshaped with @ref CLWeightsReshapeKernel.
   */
  void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output,
                 const PadStrideInfo &info, unsigned int invalid_right, unsigned int invalid_bottom,
                 const WeightsInfo &weights_info = WeightsInfo());
  /** Static function to check if given info will lead to a valid configuration of @ref
   * CLTransposeConvLayer
   *
   * @param[in] input           Input tensor info. 3 lower dimensions represent a single input,
   *                            and an optional 4th dimension for batch of inputs.
   *                            Data types supported: QASYMM8/F16/F32.
   * @param[in] weights         The 4d weights info with dimensions [width, height, IFM, OFM].
   *                            Data type supported: Same as @p input.
   * @param[in] bias            (Optional) The biases have one dimension. Data type supported:
   *                            Same as @p input.
   * @param[in] output          Output tensor info. The output has the same number of dimensions
   *                            as the @p input.
   * @param[in] info            Contains padding and policies to be used in the
   *                            transpose convolution, this is decribed in @ref PadStrideInfo.
   * @param[in] innvalid_right  The number of zeros added to right edge of the output.
   * @param[in] invalid_bottom  The number of zeros added to top edge of the output.
   * @param[in] weights_info    (Optional) Weights information needed for @ref CLConvolutionLayer,
   *                            specifies if the weights tensor has been reshaped with @ref
   *                            CLWeightsReshapeKernel.
   * @return a status
   */
  static Status validate(const ITensorInfo *input, const ITensorInfo *weights,
                         const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info,
                         unsigned int innvalid_right, unsigned int invalid_bottom,
                         const WeightsInfo &weights_info = WeightsInfo());

  // Inherited methods overridden:
  void run() override;
  void prepare() override;

private:
  CLMemoryGroup _memory_group;
  CLTransposeConvLayerUpsample _scale_f;
  CLConvolutionLayer _conv_f;
  CPPFlipWeightsKernel _flip_weights;
  CLTensor _scaled_output;
  ICLTensor *_original_weights;
  CLTensor _weights_flipped;
  bool _is_prepared;
};
}
#endif /* __ARM_COMPUTE_CLTRANSPOSECONVLAYER_H__ */